29 th Review of Atmospheric Transmission Models Meeting Aspects of Polarized Radiative Transfer, June 14 A Vector Version of the 6S Radiative Transfer.

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29 th Review of Atmospheric Transmission Models Meeting Aspects of Polarized Radiative Transfer, June 14 A Vector Version of the 6S Radiative Transfer Code for Atmospheric Correction of Satellite Data Svetlana Y. Kotchenova & Eric F. Vermote Department of Geography, University of Maryland, and NASA GSFC code 614.5

Purpose of the Creation 2 Movie credit: Blue Marble Project (by R. Stöckli) Reference: R. Stöckli, E. Vermote, N. Saleous, R. Simmon, and D. Herring (2006) "True Color Earth Data Set Includes Seasonal Dynamics", EOS, 87(5), The 6S code is a basic RT code used for the calculation of look-up tables (LUTs) in the MODIS (Moderate Resolution Imaging Spectroradiometer) atmospheric correction (AC) algorithm. Vector 6S LUTs for the AC algorithm AC of MODIS Level 1B data MOD09 (surface reflectance) different applications

History of the Code : development of 5S (Simulation of a Satellite Signal in the Solar Spectrum) by le Laboratoire dOptique Atmosphérique 1997: development of 6S (Second 5S) by Vermote et al. for further use in AC 2004: modification of the scalar 6S to account for polarization by Vermote 6SV 2005: release of a -version of 6SV by Vermote & Kotchenova 6SV1.0B 2007: release of version 1.1 of 6SV by Vermote & Kotchenova 6SV1.1 (Second Simulation of a Satellite Signal in the Solar Spectrum, Vector, version 1.1)

Technical Details 4 RT method: successive orders of scattering Polarization: the Stokes vector {I, Q, U, V = 0} Language: Fortran 77 Input file: Output file:

6SV Features 5 Spectrum: 350 to 3750 nm Molecular atmosphere: 6 code-embedded & 2 user-defined models Aerosol atmosphere: 6 code-embedded & 4 user-defined models & AERONET homogeneous & non-homogeneous with & without directional effect (10 BRDF + 1 user- defined models) Ground surface: AATSR, ALI, ASTER, AVHRR, ETM, GLI, GOES, HRV, HYPBLUE, MAS, MERIS, METEO, MSS, TM, MODIS, POLDER, SeaWiFS, VIIRS, & VGT – 19 in total Instruments:

6SV Accuracy 6 RT simulations: the number of calculation layers and angles default: 30 layers and 48 (Gaussian) angles (accuracy 0.4%) validation work: 50 layers and 148 angles Aerosol simulations: the number of scattering phase function angles default: 83 angles (including 0°, 90°, and 180°) validation work: depends on the case Accuracy-control file: paramdef.inc

6SV Validation Effort The complete 6SV validation effort is summarized in two manuscripts: S. Y. Kotchenova, E. F. Vermote, R. Matarrese, & F. Klemm, Validation of a vector version of the 6S radiative transfer code for atmospheric correction of satellite data. Part I: Path Radiance, Applied Optics, 45(26), , S. Y. Kotchenova & E. F. Vermote, Validation of a vector version of the 6S radiative transfer code for atmospheric correction of satellite data. Part II: Homogeneous Lambertian and anisotropic surfaces, Applied Optics, in press, validation against real measurements testing against benchmarks comparison with other RT codes resolution of previous 6S accuracy issues

Benchmarks (Coulsons Tables) 8 Coulsons tabulated values represent the complete solution of the Rayleigh problem for a molecular atmosphere. Standard RT code accuracy requirement: 1% Reference: Muldashev et al., Spherical harmonics method in the problem of radiative transfer in the atmosphere- surface system, Journal of Quantitative Spectroscopy and Radiative Transfer, 61 (3), , 1999.

Benchmarks (Monte Carlo) 9 Languages: Fortran, C. Limitations: large amounts of calculation time and angular space discretization. The code is written by F.M. Bréon (le Laboratoire des Sciences du Climat et de l'Environnement, France) based on the Stokes vector approach.

Previous 6S Accuracy Issues 10 Raised in: A. Lyapustin, Radiative transfer code SHARM-3D for radiance simulations over a non-Lambertian non-homogeneous surface: intercomparison study, Applied Optics, 41, (2002). 1. Inability to model aerosols with a highly-asymmetric scattering phase function 2. Incorporation of surface BRDF influence through approximate formulas resolved

Experimental Measurements 11 IKONOS reflectances corrected using AERONET and 6SV vs. reference tarp (portable brightness targets) reflectances Retrieved tarp reflectance Measured tarp reflectance The data were acquired over the Stennis Space Flight Center on February 15, Corrected MODIS Aqua water-leaving reflectances vs. MOBY water-leaving reflectances measured at = {412; 443; 490; 530; 550} nm. The MOBY data were collected off the coast of Lanai Island, Hawaii, during The analysis is done by R. Matarrese (University of Bari, Italy).

Effects of Polarization 12 Why is it so important to account for polarization? The maximum relative error is more than 7%. Example:

6SV Web Site 13

6SV Interface We provide a special Web interface which can help an inexperienced user learn how to use 6SV and build necessary input files. This interface also lets us track the number and location of 6SV users based on their IP addresses. 14

6SV Users (over the World) 15 Total: 898 users

6SV Users (in Europe) 16

6SV Users (Distribution per Country) 17 6SV distribution list: 145 users

Vector RT Codes 18 6SV RT3 Monte Carlo MODTRAN VPD available (publicly or by request) publicly not available Vector RT codes capable of simulating the reflection of solar radiation by a coupled atmosphere-surface system (top-of-atmosphere reflectance): ?

Code Comparison Project (Description) 19 SHARM (scalar) RT3 Coulsons tabulated values (benchmark) Dave Vector Vector 6S Monte Carlo (benchmark) All information on this project can be found at

Code Comparison Project (Rationale) 20 All participating codes are used in different remote sensing applications. 6SV: MODIS atmospheric correction & aerosol retrieval RT3: MODIS aerosol retrieval VPD: TOMS (Total Ozone Mapping Spectrometer) aerosol inversion SHARM: MAIAC (Multi-Angle Implementation of Atmospheric Correction for MODIS)

Code Comparison Project (Goals) 21 to illustrate the differences between individual simulations of the codes to determine how the revealed differences influence on the accuracy of atmospheric correction and aerosol retrieval algorithms ( Levy et al., Effects of neglecting polarization on the MODIS aerosol retrieval over land, IEEE Transactions on Geoscience and Remote Sensing, 42 (11), 2004 no effect on aerosol retrieval ) to create a reference (benchmark) data set The results will be summarized in a manuscript Project Web site scientific report

Code Comparison Project (Results) 22 Molecular atmosphere: done Example: TOA reflectances of the codes vs. Coulsons tabulated values for τ mol = Aerosol atmosphere: results are ready for 6SV and SHARM Mixed atmosphere: not done yet

Accuracy vs. Speed 23 Mode of 6SV1 Time, seconds Number of scattering phase function angles 83 (default) vector 4.93 (3.85) 7.24 (5.62) 8.81 (6.65) (8.20) scalar 2.39 (1.13) 3.06 (1.35) 3.71 (1.52) 4.42 (1.69) Example: Time required to simulate TOA reflectance measured by MODIS band 3 over Midway Islands (values in () show how much time is required when the pre- computed aerosol model is read from a file). Computer: Pentium 4 CPU 2.80GHz Reference: Kotchenova & Vermote, 2007

6SV Applications 24 Atmospheric correction (MODIS, VIIRS, etc.) MODIS TOA reflectanceMODIS surface reflectance The MODIS data were collected over Alta Foresta on July 16, Reference data sets for product validation Different atmospheric RT simulations

Theoretical Error Budget 25 Overall theoretical accuracy of the atmospheric correction method considering the error source on calibration, ancillary data, and aerosol inversion for three τ aer = {0.05 (clear), 0.3 (avg.), 0.5 (hazy)}: Reference: Vermote, E. F. & El Saleous, N. Z. (2006). Operational atmospheric correction of MODIS visible to middle infrared land surface data in the case of an infinite Lambertian target, In: Earth Science Satellite Remote Sensing, Science and Instruments, (eds: Qu. J. et al), vol. 1, chapter 8,

Performance of the MODIS C5 algorithms To evaluate the performance of the MODIS Collection 5 algorithms, we analyzed 1 year of Terra data (2003) over 127 AERONET sites (4988 cases in total). Methodology: 26 If the difference is within ±( ρ), the observation is good. Subsets of Level 1B data processed using the standard surface reflectance algorithm Reference data set Vector 6S AERONET measurements ( τ aer, H 2 O, particle distribution ) comparison

Validation of MOD09 (1) Comparison between the MODIS band 1 surface reflectance and the reference data set. The circle color indicates the % of comparisons within the theoretical MODIS 1-sigma error bar: green > 80%, 65% < yellow <80%, 55% < magenta < 65%, red <55%. The circle radius is proportional to the number of observations. Clicking on a particular site will provide more detailed results for this site. 27

Validation of MOD09 (2) 28 Example: Summary of the results for the Alta Foresta site. Each bar: date & time when coincident MODIS and AERONET observations are available The size of a bar: the % of good surface reflectance observations Scatter plot: the retrieved surface reflectances vs. the reference data set along with the linear fit results

Validation of MOD09 (3) In addition to the plots, the Web site displays a table summarizing the AERONET measurement and geometrical conditions, and shows a browse image of the site before and after atmospheric correction. 29 Percentage of good: band 1 – 86.62% band 5 – 96.36% band 2 – 94.13% band 6 – 97.69% band 3 – 51.30% band 7 – 98.64% band 4 – 75.18% NDVI – 97.11% EVI – 93.64% TOA MOD09-SFC Similar results are available for all MODIS surface reflectance products (bands 1-7).

Drawbacks 30 Ground Surface Ozone, Stratospheric Aerosols 8 Km 20 Km Molecules (Rayleigh Scattering) H 2 O, Tropospheric Aerosol 2-3 Km O 2, CO 2 Trace Gases 1. Compared to MODTRAN: MODTRAN Vertical variation of aerosol type 6SV Only vertical variation of aerosol profile 2. Compared to SHARM: Speed never heard any complaints except from the SHARM developer

Future Plans 31 Non-spherical particles Solution: combination of 6SV and software for the simulation of non- spherical particles (developed by T. Lapyonok et al. (AERONET group)); preliminary combination work is done by R. Levy (AERONET group). Polarized surface model Solution: in process

Thanks! 32